NAG Library Function Document

nag_ref_vec_discrete_pdf_cdf (g05exc)

1  Purpose

2  Specification

3  Description

4  References

5  Arguments

1:     p[np] – const doubleInput

On entry: the PDF or CDF of the distribution.

2:     np – IntegerInput

On entry: np is used in the calculation of the length of the reference vector.

Constraint: $\mathbf{np}\ge 1$.

3:     sizep – IntegerInput

On entry: the value of the variate, assumed to be a whole number, to which the probability in $\mathbf{p}\left[0\right]$ corresponds.

4:     distf – Nag_DiscreteDistribInput

On entry: indicates the type of information contained in p.

$\mathbf{distf}=\mathrm{Nag\_CDF}$

p contains a cumulative distribution function (CDF).

$\mathbf{distf}=\mathrm{Nag\_PDF}$

p contains a probability density function (PDF).

Constraint: $\mathbf{distf}=\mathrm{Nag\_PDF}$ or $\mathrm{Nag\_CDF}$.

5:     r – double **Output

On exit: reference vector for which memory will be allocated internally. If no memory is allocated to r (e.g., when an input error is detected) then r will be NULL on return, otherwise you should use the NAG macro NAG_FREE to free the storage allocated by r when it is no longer of use.

6:     fail – NagError *Input/Output

The NAG error argument (see Section 3.6 in the Essential Introduction).

6  Error Indicators and Warnings

NE_ALL_PROB_ZERO

All the probabilities in array p are zero.

NE_ALLOC_FAIL

Dynamic memory allocation failed.

NE_BAD_PARAM

On entry, argument distf had an illegal value.

NE_INT_ARG_LT

On entry, $\mathbf{np}=〈\mathit{\text{value}}〉$.
Constraint: $\mathbf{np}\ge 1$.

NE_NEG_PROB

At least one of the probabilities in array p is negative, $\mathbf{p}\left[〈\mathit{\text{value}}〉\right]=〈\mathit{\text{value}}〉$.

NE_NOT_INCREASING

$\mathbf{distf}=\mathrm{Nag\_CDF}$ and the sequence p is not increasing: $\mathbf{p}\left[i-1\right]=〈\mathit{\text{value}}〉$, $\mathbf{p}\left[i\right]=〈\mathit{\text{value}}〉$.

NE_PROB_NOT_ONE

The total probability is not 1, may be due to rounding errors, total probability $=〈\mathit{\text{value}}〉$.

7  Accuracy

8  Further Comments

9  Example

9.1  Program Text

Program Text (g05exce.c)

9.2  Program Data

9.3  Program Results

Program Results (g05exce.r)